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The company and a vendor teamed up to optimize the gas-lift injection process in offshore dual string oil wells in BM, Malaysia. This paper outlines how the real-time production data and well model approach help to overcome the challenges faced in dual string gas-lift wells and to improve their performance. There are many challenges to manage a brownfield specially to get high quality data. Challenges include -• Integration of various data sources, improving data quality and automation of engineering workflows.• Calculation of well Inflow Performance Relationship (IPR) as composite IPR for commingled flow when reservoir information is limited. • Evaluation of high producing Gas Oil Ratio (GOR) wells using gas-lift diagnostics.• Computation of the injected gas allocation factor in dual-string wells when both strings are producing. It was a daunting task to find technology capable of integrating the different data sources and data structures without duplicating information. In addition, the technology has to be smart enough to feed data automatically to the engineering processes and create various well monitoring reports and alarms. This is so that well KPIs (Key Performance Indicators) based on well performance analysis are always available for further diagnosis and analysis to help engineers make informed decisions at the right time.For well performance analysis, a thorough knowledge of reservoir information is essential to determine reservoir deliverability. Not every well has complete reservoir information available. A composite IPR is built at the solution node where fluid from all producing layers is commingled. This helps to manage uncertainty on the reservoir side in multiple completion wells. In high producing GOR wells, a well-model based gas-lift diagnostic technique is used to correct GOR value analyzing the gas-lift performance (GLP) curve and thus helps to optimize the gas injection rate in the well and improves the well performance. Also, in dual-string wells, the gas-lift injection allocation factor is a key element of the gaslift optimization (GLO) process as both strings have a common gas injection source (i.e. common annulus). A method is developed to compute the gas injection rate in each string, based on well tests, to determine the gas-lift injection allocation factor. Currently, this well model based method is being tested and reviewed prior to full implementation in the field.Additionally, a well-model based Virtual Metering (VM) workflow is developed to estimate daily production rates in the absence of daily flow measurements. Models are validated using the sporadic well test and both Static Gradient Survey (SGS) and Flowing Gradient Survey (FGS). Valid models are used to predict the well performance on a daily and monthly basis which ensures effective well and field monitoring and surveillance processes.

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